Energy efficient power control for the two-tier networks with small cells and massive MIMO

• Published in: 2016 IEEE Wireless Communications and Networking Conference pp. 1 - 6
• Main Authors: Ningning Lu, Yanxiang Jiang, Fuchun Zheng, Xiaohu You
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.04.2016
• Subjects: Energy efficiency; evolutionary game theory; fairness; Game theory; Games; Interference; Macrocell networks; MIMO; Optimization; Power control; two-tier networks
• ISSN: 1558-2612
• DOI: 10.1109/WCNC.2016.7564658

In this paper, energy efficient power control for the uplink two-tier networks where a macrocell tier with a massive multiple-input multiple-output (MIMO) base station is overlaid with a small cell tier is investigated. We propose a distributed energy efficient power control algorithm which allows each user in the two-tier network taking individual decisions to optimize its own energy efficiency (EE) for the multi-user and multi-cell scenario. The distributed power control algorithm is implemented by decoupling the EE optimization problem into two steps. In the first step, we propose to assign the users on the same resource into the same group and each group can optimize its own EE, respectively. In the second step, multiple power control games based on evolutionary game theory (EGT) are formulated for each group, which allows each user optimizing its own EE. In the EGT-based power control games, each player selects a strategy giving a higher payoff than the average payoff, which can improve the fairness among the users. The proposed algorithm has a linear complexity with respect to the number of subcarriers and the number of cells in comparison with the brute force approach which has an exponential complexity. Simulation results show the remarkable improvements in terms of fairness by using the proposed algorithm.